The left clip is a segment of a Hollywood movie trailed that the subject viewed while in the magnet. The right clip shows the reconstruction of this segment from brain activity measured using fMRI. The procedure is as follows: [1] Record brain activity while the subject watches several hours of movie trailers. [2] Build dictionaries (regression model) to translate between the shapes, edges and motion in the movies and measured brain activity. A separate dictionary is constructed for each of several thousand points in the brain at which brain activity was measured. (For experts: our success here in building a movie-to-brain activity encoding model was one of the keys of this study) [3] Record brain activity to a new set of movie trailers that will be used to test the quality of the dictionaries and reconstructions. [4] Build a random library of ~18000000 seconds of video downloaded at random from YouTube (that have no overlap with the movies subjects saw in the magnet). Put each of these clips through the dictionaries to generate predictions of brain activity. Select the 100 clips whose predicted activity is most similar to the observed brain activity. Average those clips together. This is the reconstruction. For a related video see: www.youtube.com For the paper (Nishimoto et al., 2011, Current Biology) go to:dx.doi.org For more information about this work, please check our lab web site:gallantlab.org
Keywords: neuroscience, brain, decoding, jack, gallant, shinji, nishimoto, fmri, berkeley
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